Research Associate or Senior Research Associate (computational modelling of renal fibrosis and inflammation)

Location: Hammersmith Campus

About the role:

This is an exciting opportunity to join the GSK–Oxford–Imperial Modelling-Informed Medicine Centre (MiMeC) and develop computational and mechanistic models of renal fibrosis and inflammation. This role will suit an ambitious researcher interested in working at the interface of computational physiology, systems biology, and translational pharmacology, developing models that capture and predict the molecular and cellular mechanisms driving chronic kidney disease progression.

This post is funded by GlaxoSmithKline Research and Development Ltd (GSK) and forms part of the MiMeC Renal Theme, which aims to establish quantitative frameworks for understanding fibrosis, inflammation, and tissue remodelling in the kidney and related organs.

You will work within Professor Steven Niederer’s computational physiology group at Imperial College London’s National Heart and Lung Institute, collaborating closely with scientists and clinicians from Imperial, Oxford, and GSK. The position offers the opportunity to combine mechanistic modelling, AI-assisted data integration, and simulation to build model-informed efficacy and safety tools for use in preclinical and clinical applications.

Please indicate in your supporting statement which job description best aligns with your background and expertise. Candidates will be considered for the appropriate level of seniority based on their experience and qualifications.

What we are looking for:

• A PhD and equivalent experience in Biomedical Engineering, Computational Physiology, Systems Biology, or a related quantitative discipline.
• Experience in mechanistic or multi-scale modelling of biological, physiological, or fibrotic systems.
• Knowledge of renal physiology, fibrosis, inflammation, or related organ-level disease processes.
• Strong computational and analytical skills, with proficiency in Python or Julia.
• Experience in statistical modelling, parameter estimation, or uncertainty quantification (e.g. Bayesian inference or global sensitivity analysis).
• Interest in translational pharmacology, fibrosis modelling, or drug discovery applications, and a willingness to engage with industrial and academic collaborators.
• Excellent communication skills and a strong publication record.

Desirable:

• Experience integrating experimental, preclinical, or clinical datasets into models of fibrosis or chronic disease.
• Familiarity with AI/ML methods for model calibration, emulation, or data-driven discovery.
• Prior experience in open-source software development and collaborative codebases (e.g. GitHub).

What you would be doing

• Developing and applying multiscale computational models to describe mechanisms of renal fibrosis, inflammation, and tissue remodelling.
• Integrating in vitro, in vivo, and clinical data to connect molecular and cellular pathways to organ-level functional decline.
• Applying statistical, AI, and machine-learning methods for model calibration, validation, and uncertainty quantification.
• Working closely with collaborators at GSK, Oxford, and Imperial to align model outputs with preclinical and clinical efficacy studies.
• Delivering reproducible, open-source modelling tools and publishing results in high-impact scientific journals.
• Presenting findings to internal and external stakeholders and contributing to collaborative project planning.

What we can offer you:

• Supporting you in developing your career into an independent researcher at a world-leading institution
• Working with the Cardiac Electro-Mechanics Research Group led by Prof. Steven Niederer
• Sector-leading salary and remuneration package (including 39 days off a year)

Further Information

The is a full-time, fixed-term role for 3 years with the possibility of an extension.

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